Why every chief marketing officer needs to become a CMDO

JUL. 15, 2024

Lumenalta

Modern consumers want it all from brands: personalized experiences, superfast service, and authentic storytelling.

To meet these expectations, the Chief Marketing Officer’s (CMO) mandate is clear in theory: combine creativity with data to wow customers and fuel growth. In practice, this means CMOs must become CMDOs: Chief Marketing Data Officers.

CMDOs operate at the intersection of imagination and information. They think creatively and know their numbers. They jump between storytelling and spreadsheets daily. They know that modern marketing is art and science — and they’re masters of both.

As AI and analytics redefine marketing, CMOs face a critical choice: embrace the role of CMDO or risk falling behind. This article outlines what it takes to transform yourself and your team.

Effective marketing requires data literacy in the AI age

The days of “Mad Men” marketers relying on gut instincts are gone. Data-driven marketing isn’t new, but the “D” in CMDO goes beyond number-crunching and report-pulling.

Marketing teams must be proficient in AI and machine learning (ML) to extract insights from customer data without relying on other departments. This starts with the CMDO.

Essential skills and competencies of the CMDO

CMDOs need a unique blend of technical, analytical, and creative skills:

Data science and AI/ML proficiency

CMDOs understand data science principles and AI/ML techniques. They interpret data, identify patterns, and use AI/ML tools for insights.

Storytelling and data visualization

CMDOs can translate insights into narratives that resonate with customers using visualization tools to create easily digestible representations of complex information.

Martech mastery

CMDOs are well-versed in marketing technologies and integrating AI/ML into their tech stack. They can distinguish useful new tools from shiny objects and optimize their use for marketing performance.

Cross-functional collaboration

CMDOs can work as easily with data scientists and IT professionals as with creative teams. They shape culture and inspire others by championing data-driven decision-making, experimentation, and AI/ML technologies.

Developing these CMDO skills requires formal education, hands-on experimentation, and continuous learning.

First, assess your current abilities. Identify knowledge gaps to set learning objectives. Then, invest in formal education like data science or AI/ML certifications to build a strong foundation. You can also collaborate with cross-functional teams and experiment with AI/ML tools in small-scale projects for practical experience.

Transform culture, talent, and teams

After transforming themselves, CMDOs need to upskill their teams. They want “T-shaped” marketers — people who combine deep expertise in a specific discipline with broad analytical and AI skills.

T-shaped marketers should be comfortable with large datasets, statistical concepts, and analytics tools to derive actionable insights. They also need a basic understanding of AI and machine learning principles, such as supervised and unsupervised learning, neural networks, and natural language processing.

“Everywhere we look AI is breaking down the silos that have traditionally sat between art and science — arming marketers, developers, and data scientists alike with helpful assistants to help close their perceived gaps [...] The common theme we all need to embrace is breaking out of our silos, adopting new technologies, and being willing to flex above and beyond our historically articulated roles,” says Christi Sodano, CMO at Lumenalta.

Creating these skills on a marketing team requires an ongoing cultural transformation program:

Immersive training

CMDOs should partner with HR to implement hands-on training covering data, AI, and modern marketing practices. Methods like lunch-and-learns, hackathons, and job rotations can help marketers gain practical AI experience.

Strategic hiring

Not everything can be taught in-house. Adding specialists like data scientists, machine learning engineers, and marketing automation experts can enhance the team’s expertise and performance.

“Fusion” teams

Assemble cross-functional squads with marketers, data scientists, engineers, and product experts for high-impact projects requiring diverse skill sets and perspectives.

Establish data governance

Implement data governance policies and processes to ensure data quality, security, and compliance for information collection, storage, and usage.

Modern storytelling happens with AI and numbers

Insights don’t captivate audiences — stories do. But numbers inform narratives, and the CMDO knows how to use data and AI to tell stories that educate, entertain, and engage customers.

“Data isn’t the same as knowledge. Data without context is no more useful than knowing your current driving speed without understanding which direction the car is headed.” – Casey Carey, Director of Platforms & Publisher Marketing, Google (source)

Here are ways modern marketing teams use AI and data to tell their brands’ stories:

Natural language processing (NLP)

NLP algorithms can analyze online conversations, reviews, search data, and social interactions to understand the customer’s authentic voice. You can use these insights to tell stories in a style and tone that matches your target audience’s language.

Computer vision

Computer vision analyzes visual content to find your brand’s best-performing formats, themes, and creative elements. By looking at content across social media and other channels, you can uncover the key drivers of engagement and improve your visual narratives.

Sentiment analysis

Monitor sentiment across touchpoints, such as social media, product reviews, and surveys. Use these insights to adjust brand stories to better connect with your customers.

AI content creation

Generative AI tools can create personalized marketing content, such as emails, social media posts, and ad campaigns. These tools tailor the content to specific customer segments based on their preferences and behaviors, ensuring each group receives relevant and engaging messages.

Predictive analytics

Marketers can anticipate future customer needs based on historical purchases and behavioral data. This insight enables the development of targeted brand stories that guide customers through their buying journey.

CMDO inspiration: New storytelling forms enabled by data and AI

Spotify’s “Wrapped” campaign turns listener data into interactive stories that highlight users’ top songs, genres, and "music twins.” In 2023, Spotify introduced new features to Wrapped. These included “Me in 2023,” which assigns users a character based on their listening habits, and “Sound Town,” which matches users to a city based on their music preferences.

Nike’s “Nike By You” platform analyzes user preferences, purchase history, and trends to provide shoe design suggestions and customization options. Customers can choose colors, materials, and patterns and add personalized text. Nike also uses computer vision to analyze customer-uploaded images and suggest color schemes based on personal style.

Dove’s “Campaign for Real Beauty” started in 2004. Recently, it got an AI twist: Dove pledged never to use AI-generated images in their ads. They also released the Real Beauty Prompt Playbook, a free tool to help creators and brands produce inclusive and diverse visual content. This initiative aims to counteract biases in AI-generated imagery and promote a realistic and inclusive portrayal of beauty.

AI and machine learning transform marketing ops

“AI won’t replace humans — but humans with AI will replace humans without AI” has become somewhat of a maxim. The same is true of marketing teams.

CMDOs must embed new AI capabilities in their marketing operations to stay competitive. Implementing AI tools for individual use cases isn’t enough. Without integration across teams and their tools, there is a risk of creating siloed data, biased algorithms, and inconsistent output.

Give the marketing lifecycle an AI/ML makeover

Once you embed AI/ML capabilities across the marketing lifecycle, CMDOs can orchestrate marketing at a scale, speed, and precision our “Mad Men” predecessors would find hard to imagine.

Planning and strategy

AI-powered predictive analytics help CMDOs process and analyze historical data, market trends, competitor activities, and macroeconomic variables. They can uncover hidden patterns, anticipate trends, and identify the most promising strategies, channels, content types, and audience targets.

This AI-assisted approach to planning and strategy makes marketing teams more agile, responsive, and innovative.

Content ideation and creation

Generative AI tools like GPT-4, Claude, and Midjourney can assist in creating content assets. These services can generate high-quality drafts of blog posts, social media updates, ad copy, and videos by training on a brand’s existing library and style guide.

AI-powered insights can also guide the creative process so that content ideas are grounded in customer preferences and behavior.

Audience engagement and retention

AI can improve audience engagement and retention in several ways:

Analyze customer data, including demographics, behavior, preferences, and sentiment.
Create dynamic buyer personas for targeted messaging and personalized experiences.
Identify high-quality leads and nurture them through chatbots and email campaigns.
Predict churn risk, identify upsell and cross-sell opportunities, and optimize customer engagement and lifetime value.

Delivery optimization

AI-powered platforms can automate media buying, adjust audience targeting, and optimize ad placements based on real-time performance data across multiple channels.

Dynamic creative optimization (DCO) tailors ad content and formats to individual users based on preferences, context, and behavior. This technology ensures that each customer receives the most relevant message, improving conversion rates and campaign performance.

Performance measurement

AI-powered platforms automatically collect and unify data from various sources, identify patterns, and attribute conversions to the most influential channels. AI can also forecast campaign results, allowing CMDOs to adjust strategies and resources proactively.

Build an AI/ML marketing stack

This AI-driven marketing lifecycle needs a tech stack designed for speed and agility — very different from legacy, siloed martech. Here’s an overview of tools that typically make up this modular architecture so you can add new capabilities without disassembling the entire stack.

Data management and analytics tools

A robust set of data management and analytics tools is the foundation for collecting actionable customer insights and making data-driven decisions.

Customer data platforms (CDPs) like Segment collect and unify data from various touchpoints.
Cloud data warehouses like Snowflake are used for large-scale data processing and storage.
Business Intelligence (BI) tools like Looker enable data visualization and surface critical insights for data-driven decision-making.

AI/ML enablement tools

Specialized platforms and tools streamline the development, deployment, and management of advanced analytics models.

Databricks and other data science workbenches and experimentation tools form the infrastructure for building and deploying advanced analytics models.
Platforms like DataRobot automate the process of building, testing, and deploying machine learning models, making it easier for marketing teams to leverage AI without extensive data science expertise.
Commercial and custom machine learning algorithms are used for specific use cases, like predictive targeting or dynamic pricing.

Intelligent content tools

AI-powered tools can generate, optimize, and distribute personalized content.

AI engines like OpenAI’s GPT-4 create tailored content at scale, such as personalized email campaigns or product descriptions.
Dynamic content hubs and management systems like Adobe Experience Manager organize and deliver content across channels.
Conversational AI and dialog management tools, like Google’s Dialogflow and Amazon’s Lex, enable chatbots and virtual assistants for personalized, interactive experiences.

Marketing automation and delivery tools

Automation and delivery tools can streamline processes, optimize performance, and provide actionable insights for executing campaigns.

Marketing automation platforms, such as Salesforce Marketing Cloud, help manage complex, multichannel campaigns.
Dynamic creative optimization and content recommendation engines, like Adobe Target, ensure customers get the most relevant content and offers.
Ad performance optimization solutions and omnichannel attribution models, such as Google Analytics 360, measure and optimize marketing investments.

Analytical power still needs to be balanced with human creativity

In a world of algorithms and automation, it’s tempting to think that machines will soon master marketing. But as the CMDO knows, marketing involves human nuance that even the most advanced AI can’t replicate.

Balancing quantitative and qualitative, analytical and artistic, automation and ingenuity — this is the defining challenge for marketing leaders. CMDOs can propel marketing into a new golden age of customer-centricity, purposeful storytelling, and business growth by using data and AI for resonance, meaning, and authenticity.